Students analyze two North Pole orthographic data visualizations produced from soil moisture data. After describing trends in the seasonal thaw of land surfaces, students demonstrate their understanding of Earth’s energy budget by explaining relationships and make predictions about the dataset.

Students explore the spatial patterns observed in meteorological data and learn how this information is used to predict weather and understand climate behavior.

In this activity, students use satellite images from the NASA Landsat team to quantify changes in glacier cover over time from 1986 to 2018. 

Students explore albedo, sea ice, and the relationship between changing albedo and changing sea ice using data visualizations. 

Arctic sea ice is the cap of frozen seawater blanketing most of the Arctic Ocean and neighboring seas in wintertime. It follows seasonal patterns of thickening and melting. Students view how the quantity has changed from 1979 through 2018. 

Students examine the two time series images to determine the differences between seasonal ice melt over water versus land.

Students connect day/night and seasonal cycles with albedo in the Arctic region. 

The advance-and-retreat cycle of snow cover drastically changes the whiteness and brightness of Earth. Using two maps created using NASA satellite data for 2017, students review the seasonal differences of snow and ice extent and answer questions on their observations.

This series of videos highlights how NASA Climate Scientists use mathematics to solve everyday problems.  These educational videos to illustrate how math is used in satellite data analysis. 

Students will make a claim about whether changing albedo contributes to changes in Arctic habitats.